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Relationship: 724


The title of the KER should clearly define the two KEs being considered and the sequential relationship between them (i.e., which is upstream and which is downstream). Consequently all KER titles take the form “upstream KE leads to downstream KE”.  More help

Binding, Tubulin leads to Altered, Chromosome number

Upstream event
Upstream event in the Key Event Relationship. On the KER page, clicking on the Event name under Upstream Relationship will bring the user to that individual KE page. More help
Downstream event
Downstream event in the Key Event Relationship. On the KER page, clicking on the Event name under Upstream Relationship will bring the user to that individual KE page. More help

Key Event Relationship Overview

The utility of AOPs for regulatory application is defined, to a large extent, by the confidence and precision with which they facilitate extrapolation of data measured at low levels of biological organisation to predicted outcomes at higher levels of organisation and the extent to which they can link biological effect measurements to their specific causes. Within the AOP framework, the predictive relationships that facilitate extrapolation are represented by the KERs. Consequently, the overall WoE for an AOP is a reflection in part, of the level of confidence in the underlying series of KERs it encompasses. Therefore, describing the KERs in an AOP involves assembling and organising the types of information and evidence that defines the scientific basis for inferring the probable change in, or state of, a downstream KE from the known or measured state of an upstream KE. More help

AOPs Referencing Relationship

This table is automatically generated upon addition of a KER to an AOP. All of the AOPs that are linked to this KER will automatically be listed in this subsection. Clicking on the name of the AOP in the table will bring you to the individual page for that AOP. More help
AOP Name Adjacency Weight of Evidence Quantitative Understanding Point of Contact Author Status OECD Status
Chemical binding to tubulin in oocytes leading to aneuploid offspring non-adjacent High Cataia Ives (send email) Open for citation & comment EAGMST Under Review

Taxonomic Applicability

Select one or more structured terms that help to define the biological applicability domain of the KER. In general, this will be dictated by the more restrictive of the two KEs being linked together by the KER. Authors can indicate the relevant taxa for this KER in this subsection. The process is similar to what is described for KEs (see pages 30-31 and 37-38 of User Handbook) More help
Term Scientific Term Evidence Link
Homo sapiens Homo sapiens Moderate NCBI
mouse Mus musculus High NCBI
rat Rattus norvegicus Moderate NCBI

Sex Applicability

Authors can indicate the relevant sex for this KER in this subsection. The process is similar to what is described for KEs (see pages 31-32 of the User Handbook). More help
Sex Evidence
Mixed High

Life Stage Applicability

Authors can indicate the relevant life stage for this KER in this subsection. The process is similar to what is described for KEs (see pages 31-32 of User Handbook). More help
Term Evidence
All life stages Moderate

Key Event Relationship Description

Provide a brief, descriptive summation of the KER. While the title itself is fairly descriptive, this section can provide details that aren’t inherent in the description of the KEs themselves (see page 39 of the User Handbook). This description section can be viewed as providing the increased specificity in the nature of upstream perturbation (KEupstream) that leads to a particular downstream perturbation (KEdownstream), while allowing the KE descriptions to remain generalised so they can be linked to different AOPs. The description is also intended to provide a concise overview for readers who may want a brief summation, without needing to read through the detailed support for the relationship (covered below). Careful attention should be taken to avoid reference to other KEs that are not part of this KER, other KERs or other AOPs. This will ensure that the KER is modular and can be used by other AOPs. More help

In this KER, chemicals that bind to tubulin indirectly lead to altered chromosome numbers. This is because tubulin binding by chemicals interferes with tubulin polymerization leading to microtubule depolymerization, abnormal spindle structure/morphology and subsequent chromosome mis-segregation. The relationship is indirect because there are no studies that have measured all KEs leading up to the AO. However, as described in more details below, there are plenty of studies showing that exposure to spindle poisons induces aneuploidy in female germ cells. This relationship has been shown in vitro and in vivo, and in somatic cells as well as in germ cells.

Evidence Supporting this KER

Assembly and description of the scientific evidence supporting KERs in an AOP is an important step in the AOP development process that sets the stage for overall assessment of the AOP (see pages 49-56 of the User Handbook). To do this, biological plausibility, empirical support, and the current quantitative understanding of the KER are evaluated with regard to the predictive relationships/associations between defined pairs of KEs as a basis for considering WoE (page 55 of User Handbook). In addition, uncertainties and inconsistencies are considered. More help


Biological Plausibility
Define, in free text, the biological rationale for a connection between KEupstream and KEdownstream. What are the structural or functional relationships between the KEs? For example, there is a functional relationship between an enzyme’s activity and the product of a reaction it catalyses. Supporting references should be included. However, it is recognised that there may be cases where the biological relationship between two KEs is very well established, to the extent that it is widely accepted and consistently supported by so much literature that it is unnecessary and impractical to cite the relevant primary literature. Citation of review articles or other secondary sources, like text books, may be reasonable in such cases. The primary intent is to provide scientifically credible support for the structural and/or functional relationship between the pair of KEs if one is known. The description of biological plausibility can also incorporate additional mechanistic details that help inform the relationship between KEs, this is useful when it is not practical/pragmatic to represent these details as separate KEs due to the difficulty or relative infrequency with which it is likely to be measured (see page 40 of the User Handbook for further information).   More help

Accurate chromosome segregation requires the temporally regulated and coordinated interaction of many cellular components including protein kinases and phosphatases, topoisomerases, the anaphase-promoting complex (APC), proteasomes, mitotic and meiotic spindle, centrosomes and kinetochores [Orr et al., 2015]. Disruption of any of these processes by chemicals can potentially result in aneuploidy [Parry et al., 2002]. There is extensive knowledge of cellular processes associated with chromosome segregation in both somatic cells [Collin et al., 2013; London et al., 2014; Musacchio, 2015] and germ cells [Polanski, 2013; Touati and Wassmann, 2016; Bennabi et al., 2016]. Although many of these cellular components and processes are shared between somatic cells and germ cells, there are features that are unique to germ cells, in general, and female germ cells specifically [Hunt and Hassold, 2002; Webster and Schuh, 2017].

Unique to germ cells are the processes that take place during the first meiotic division when homologous chromosomes must segregate to opposite poles of the cell. Homologous chromosome segregation is possible because they are paired in bivalents physically attached at chiasmata and the sister kinetochores of each chromosome are held together by complexes of cohesion proteins, behaving as a unique monooriented structure with respect to spindle microtubules [reviewed by Eichenlaub-Ritter, 2012]. This is at variance with the second meiotic division and mitotic division when segregation involves the two sister chromatids of each chromosome. Different mechanisms have been proposed to cause aneuploidy in germ cells, including: (1) nondisjunction of homologous chromosomes; (2) premature separation of homologous chromosomes or sister chromatids; and (3) recombination defects [Nagaoka et al., 2012; Zelazowski et al., 2017]. Each of these mechanisms interacts and contributes to the genesis of aneuploidy through a complex interplay of molecular and cellular events [Nagaoka et al., 2012]. Unique to female germ cells is also the formation of the meiotic spindle in the absence of centrioles, as described before, and the reduced stringency of the SAC that allows progression of meiosis even in the presence of misaligned chromosomes, and the long time that oocytes are arrested at the end of meiotic prophase with possible progressive degradation of cohesion proteins [Hunt and Hassold, 2002; Nagaoka et al., 2012; Webster and Schuh, 2017].

This KER indirectly links chemical binding to tubulin to aneuploidy. A diverse array of chemical agents are well established to induce aneuploidy, with the majority of these agents operating through binding to tubulin to impair spindle function, chromosome dynamics and ultimately segregation [reviewed in Parry et al., 2002; and in Pacchierotti and Eichenlaub-Ritter, 2011]. However, an extensive amount of work in this field has focused on gametes thus, we focus on chemically-induced aneuploidy in germ cells. For a summary of chemically-induced aneuploidy in somatic cells the reader is referred to a few key reviews [e.g., Adler, 1993; Leopardi et al., 1993; Aardema et al., 1998].

There is extensive evidence in mammalian models that chemicals can induce aneuploidy by interfering with the proper functioning of the meiotic spindle and other aspects of chromosome segregation. The aneugenic activity of microtubule disrupting agents was also recently demonstrated using a Caenorhabditis elegans screening platform for the rapid assessment of chemical effects on germline function [Allard et al., 2013]. About 20 chemicals have been shown to induce aneuploidy in mammalian oocytes in vivo and the majority of these chemicals are tubulin binders (i.e., they interfere with microtubule dynamics through tubulin binding during meiosis) [Mailhes and Marchetti, 1994, 2005; Pacchierotti and Eichenlaub-Ritter, 2011]. Collectively, these studies suggest that the main window for the induction of aneuploidy in oocytes is restricted to the periovulation period with a peak of sensitivity around the resumption of meiosis and the induction of ovulation. Depending on dose and time, spindle inhibitors can induce aneuploidy in almost 100% of oocytes [reviewed in Mailhes and Marchetti, 2005], suggesting that the disruption of microtubule and spindle dynamics is a very sensitive target for the induction of aneuploidy in female germ cells. Although the majority of the available studies investigated the induction of aneuploidy during meiosis I, there is evidence that the two meiotic divisions have similar sensitivity to chemically-induced aneuploidy [Marchetti et al., 1996].

Uncertainties and Inconsistencies
In addition to outlining the evidence supporting a particular linkage, it is also important to identify inconsistencies or uncertainties in the relationship. Additionally, while there are expected patterns of concordance that support a causal linkage between the KEs in the pair, it is also helpful to identify experimental details that may explain apparent deviations from the expected patterns of concordance. Identification of uncertainties and inconsistencies contribute to evaluation of the overall WoE supporting the AOPs that contain a given KER and to the identification of research gaps that warrant investigation (seep pages 41-42 of the User Handbook).Given that AOPs are intended to support regulatory applications, AOP developers should focus on those inconsistencies or gaps that would have a direct bearing or impact on the confidence in the KER and its use as a basis for inference or extrapolation in a regulatory setting. Uncertainties that may be of academic interest but would have little impact on regulatory application don’t need to be described. In general, this section details evidence that may raise questions regarding the overall validity and predictive utility of the KER (including consideration of both biological plausibility and empirical support). It also contributes along with several other elements to the overall evaluation of the WoE for the KER (see Section 4 of the User Handbook).  More help

We are not aware of any chemical that bind to tubulin and does not cause aneuploidy, providing that a high enough dose/concentration was tested.

Response-response Relationship
This subsection should be used to define sources of data that define the response-response relationships between the KEs. In particular, information regarding the general form of the relationship (e.g., linear, exponential, sigmoidal, threshold, etc.) should be captured if possible. If there are specific mathematical functions or computational models relevant to the KER in question that have been defined, those should also be cited and/or described where possible, along with information concerning the approximate range of certainty with which the state of the KEdownstream can be predicted based on the measured state of the KEupstream (i.e., can it be predicted within a factor of two, or within three orders of magnitude?). For example, a regression equation may reasonably describe the response-response relationship between the two KERs, but that relationship may have only been validated/tested in a single species under steady state exposure conditions. Those types of details would be useful to capture.  More help

It is difficult to compare the response-response relationship between these two KEs, as binding to tubuline (KEupstream) is generally measured in an acellular system or in vitro, while altered chromosome nubmer (KEdownstream) is measured in vivo. However, Brunner et al. [1991] and Wallin and Hartely-Asp [1993] analyzing the ability of 10 chemicals to interfere with microtubule assembly reported that there is a good correlation between the efficiency of microtubule assembly interference and the anuegenic potential of each chemical. That is, chemicals that interfered with microtubule assembly at low concentrations are strong aneugens (eg, colchicine, vinblastine); while chemicals that did not affect the steady state of microtubule assembly do not induced aneuploidy or are very weak inducers (eg, diazepam, cadmium chloride).

This sub-section should be used to provide information regarding the approximate time-scale of the changes in KEdownstream relative to changes in KEupstream (i.e., do effects on KEdownstream lag those on KEupstream by seconds, minutes, hours, or days?). This can be useful information both in terms of modelling the KER, as well as for analyzing the critical or dominant paths through an AOP network (e.g., identification of an AO that could kill an organism in a matter of hours will generally be of higher priority than other potential AOs that take weeks or months to develop). Identification of time-scale can also aid the assessment of temporal concordance. For example, for a KER that operates on a time-scale of days, measurement of both KEs after just hours of exposure in a short-term experiment could lead to incorrect conclusions regarding dose-response or temporal concordance if the time-scale of the upstream to downstream transition was not considered. More help

Binding to tubulin is occurring on the time scale seconds (acellular systems) and minutes (in vitro). In vivo, the time-scale is determined by the route of administration and the ADME characteristics of the chemical. For the induction of aneuploidy, chemical binding to tubulin must occur within a short time range before the completion of the first meiotic division. Mailhes and Yuan [1987] showed that the induction of aneuploid oocytes following exposure to colchicine is maximum when administered 12 hr before ovulation and is reduced when given more or less than 12 hours.

Known modulating factors
This sub-section presents information regarding modulating factors/variables known to alter the shape of the response-response function that describes the quantitative relationship between the two KEs (for example, an iodine deficient diet causes a significant increase in the slope of the relationship; a particular genotype doubles the sensitivity of KEdownstream to changes in KEupstream). Information on these known modulating factors should be listed in this subsection, along with relevant information regarding the manner in which the modulating factor can be expected to alter the relationship (if known). Note, this section should focus on those modulating factors for which solid evidence supported by relevant data and literature is available. It should NOT list all possible/plausible modulating factors. In this regard, it is useful to bear in mind that many risk assessments conducted through conventional apical guideline testing-based approaches generally consider few if any modulating factors. More help

As described above, time of exposure with respect to ovulation is a modulating factor.

Known Feedforward/Feedback loops influencing this KER
This subsection should define whether there are known positive or negative feedback mechanisms involved and what is understood about their time-course and homeostatic limits? In some cases where feedback processes are measurable and causally linked to the outcome, they should be represented as KEs. However, in most cases these features are expected to predominantly influence the shape of the response-response, time-course, behaviours between selected KEs. For example, if a feedback loop acts as compensatory mechanism that aims to restore homeostasis following initial perturbation of a KE, the feedback loop will directly shape the response-response relationship between the KERs. Given interest in formally identifying these positive or negative feedback, it is recommended that a graphical annotation (page 44) indicating a positive or negative feedback loop is involved in a particular upstream to downstream KE transition (KER) be added to the graphical representation, and that details be provided in this subsection of the KER description (see pages 44-45 of the User Handbook).  More help

No known feedback loops. 

Domain of Applicability

As for the KEs, there is also a free-text section of the KER description that the developer can use to explain his/her rationale for the structured terms selected with regard to taxonomic, life stage, or sex applicability, or provide a more generalizable or nuanced description of the applicability domain than may be feasible using standardized terms. More help

Data for this KER are available in vitro and in vivo, and in a variety of mammalian species including humans.


List of the literature that was cited for this KER description using the appropriate format. Ideally, the list of references should conform, to the extent possible, with the OECD Style Guide (OECD, 2015). More help

Aardema MJ, Albertini S, Arni P, Henderson LM, Kirsch-Volders M, Mackay JM, Sarrif AM, Stringer DA, Taalman RD. 1998. Aneuploidy: a report of an ECETOC task force. Mutat Res 410:3-79.

Adler ID. 1993. Synopsis of the in vivo results obtained with the 10 known or suspected aneugens tested in teh CEC collaborative study. Mutat Res 287:131-137.

Allard P, Kleinstreuer NC, Knudsen TB, Colaiacovo MP. 2013. A C. elegans screening platform for the rapid assessment of chemical disruption of germline function. Environ Health Perspect 121:717–724.

Bennabi I, Terret ME, Verlhac MH. 2016. Meiotic spindle assembly and chromosome segregation in oocytes. J Cell Biol 215:611-619.

Brunner M, Albertini S, Würgler FE. 1991. Effects of 10 known or suspected spindle poisons in the in vitro porcine brain tubulin assembly assay. Mutagen 6:65-70.

Cammerer Z, Schumacher MM, Kirsch-Volders M, Suter W, Elhajouji A. 2010. Flow cytometry peripheral blood micronucleus test in vivo: determination of potential threshold for aneuploidy induced by spindle poisons. Environ Mol Mutagen 51:278-284.

Collin P, Nashchekina O, Walker R, Pines J. 2013. The spindle assembly checkpoint works like a rheostat rather than a toggle switch. Nat Cell Biol 15:1378–1385.

Eichenlaub-Ritter U. 2012. Female meiosis and beyond: more questions than answers? Reprod Biomed Online 24:589-590.

Elhajouji A, Lukamowicz M, Cammerer Z, Kirsch-Volders M. 2011. Potential thresholds for genotoxic effects by micronucleus scoring. Mutagenesis 26:199-204.

Hassold T, Hall H, Hunt P. 2007. The origin of human aneuploidy: Where we have been, where we are going. Hum Mol Genet 16: R203–R208.

Hummler E, Hansmann I. 1985. Preferential nondisjunction of specific bivalents in oocytes from Djungarian hamsters (Phodopus sungorus) following colchicine treatment. Cytogenet Cell Genet 39:161–167.

Hunt PA, Hassold TJ. 2002. Sex matters in meiosis. Science 296:2181–2183.

Leopardi P, Zijno A, Bassani B, Pacchierotti F. 1993. In vivo studies on chemically induced aneuploidy in mouse somatic and germinal cells. Mutat Res 287:119-130.

London N, Biggins S. 2014. Signalling dynamics in the spindle checkpoint response. Nat Rev Mol Cell Biol 15:736–747.

Mailhes JB, Marchetti F. 1994. The influence of postovulatory ageing on the retardation of mouse oocyte maturation and chromosome segregation induced by vinblastine. Mutagenesis 9:541–545.

Mailhes JB, Marchetti F. 2005. Mechanisms and chemical induction of aneuploidy in rodent germ cells. Cytogenet Genome Res 111: 384–391.

Mailhes JB, Yuan ZP. 1987. Differential sensitivity of mouse oocytes to colchicine-induced aneuploidy. Environ Mol Mutagen 10:183–188.

Mailhes JB, Preston RJ, Yuan ZP, Payne HS. 1988. Analysis of mouse metaphase II oocytes as an assay for chemically induced aneuploidy. Mutat Res 198:145–152.

Mailhes JB, Yuan ZP, Aardema MJ. 1990. Cytogenetic analysis of mouse oocytes and one-cell zygotes as a potential assay for heritable germ cell aneuploidy. Mutat Res 242:89–100.

Marchetti F, Mailhes JB, Bairnsfather L, Nandy I, London SN. 1996. Dose-response study and threshold estimation of griseofulvininduced aneuploidy during female mouse meiosis I and II. Mutagenesis 11:195–200.

Midgley AR, Pierce B, Dixon FJ. 1959. Nature of colchicine resistance in golden hamster. Science 130:40–41.

Musacchio A. 2015. The molecular biology of spindle assembly checkpoint signaling dynamics. Curr Biol 25:R1002-R1018.

Nagaoka SI, Hodges CA, Albertini DF, Hunt PA. 2011. Oocyte-specific differences in cell-cycle control create an innate susceptibility to meiotic errors. Curr Biol  21:651-657.

Nagaoka SI, Hassold TJ, Hunt PA. 2012. Human aneuploidy: Mechanisms and new insights into an age-old problem. Nat Rev Genet 13:493–504.

Orr B, Godek KM, Compton D. 2015. Aneuploidy. Curr Biol 25:R523-548.

Pacchierotti F, Eichenlaub-Ritter U. 2011. Environmental hazard in the aetiology of somatic and germ cell aneuploidy. Cytogenet Genome Res 133:254-268.

Parry EM, Parry JM, Corso C, Doherty A, Haddad F, Hermine TF, Johnson G, Kayani M, Quick E, Warr T, Williamson J. 2002. Detection and characterization of mechanisms of action of aneugenic chemicals. Mutagenesis 17:509-21.

Polanski Z. 2013. Spindle assembly checkpoint regulation of chromosome segregation in mammalian oocytes. Reprod Fertil Dev 25:472-483

Sugawara S, Mikamo K. 1980. An experimental approach to the analysis of mechanisms of meiotic nondisjunction and anaphase lagging in primary oocytes. Cytogenet Cell Genet 28:251-264.

Tease C, Fisher G. 1986. Oocytes from young and old female mice respond differently to colchicine. Mutat Res 173:31–34.

Touati SA, Wassmann K. 2016. How oocytes try to get it right: spindle checkpoint control in meiosis. Chromosoma 125:321-335.

Wallin M, Hartley-Asp B. 1993. Effects of potential aneuploidy inducing agents on microtubule assembly in vitro. Mutat Res 287:17-22.

Webster A, Schuh M. 2017. Mechanisms of aneuploidy in human eggs. Trends Cell Biol 27:55-68.

Zelazowski MJ, Sandoval M, Paniker L, Hamilton HM, Han J, Gribbell MA, Kang R, Cole F. 2017. Age-Dependent Alterations in Meiotic Recombination Cause Chromosome Segregation Errors in Spermatocytes. Cell 171:601-614